Sensors to Cloud Architectures Workshop (SCAW-2017)

Sensors to Cloud Architectures Workshop (SCAW-2017)

February 4th 2017

 

Austin, Texas, USA
Held in conjunction with HPCA-23

http://hpca2017.org/

 

Call for papers

Organizing Chairs:

Ramesh Illikkal             Intel                                       ramesh.g.illikkal@intel.com

Ravi Iyer                         Intel                                       ravishankar.iyer@intel.com

Yuhao Zhu                    University of Texas, Austin          yzhu@utexas.edu

 

Overview
The computer industry is witnessing an inflection point – ‘Internet of Things combined with Cloud Analytics’ –which has implications from end (sensor devices) to end (cloud architectures). Many technologies come together contributing to this major inflection point: Computing platforms getting smaller (e.g. handheld devices, wearables), richer (e.g. image and language understanding) and broader (i.e. reaching the masses via Internet of Things). Sensors operating in constrained environments connected through intelligent gateways and cloud backend creates a very complex environment for the operators, system integrators, and developers of this new emerging technology. Discovering and managing sensor devices; collecting, cleaning and storing discoverable data; normalizing, aggregating and analyzing the data for insights and actions; managing the security and privacy of the data, enforcing the access privileges and trusted execution environments – all these are required to make this revolution happen.

The research challenges in IoT platforms are multi-fold: (a) providing rich functionality and wider power/performance range for sensor devices (b) attempting to cover a broad range of applications that can be migrated from cloud to gateways and sensor devices, (c) enabling a scalable and modular cloud architecture that provides the required real-time and uptime capabilities and (d) providing a rich software programming environment that eases the challenge of developing applications on end to end platforms consisting of elements ranging from sensors to gateways to cloud. The goal of this workshop is to bring together academic researchers and industry practitioners to discuss future IoT sensor-to- cloud architectures including sensors, gateways and cloud architectures.

Program

8:30 AM 8:35 AM                                               Welcome & Workshop Introduction       
8:35 AM 9:35 AM   Keynote:  Microsoft’s Production Reconfigurable Cloud Dr. Derek Chiou Microsoft
UT Austin
9:35 AM 10:00 AM   Towards Optimal Workload & Bandwidth Distribution for 3D Sensing Networks Javier Felip, David Gonzalez-Aguirre and Omesh Tickoo Intel Labs, Intel Corporation
10:00 AM 10:30 AM                                                                        Break
10:30 AM 10:55 AM   Implementing Stochastic Hopfield-Network-based Linear Solvers on a Hardware-Constrained Neural Substrate Erik Jorgensen, Rohit Shukla, and
Mikko Lipasti
Department of Electrical and Computer Engineering
University of Wisconsin-Madison
10:55 AM 11:20 AM   Implementation of Large triangular matrix decomposition and solver for EKF in heterogeneous embedded-vision system Yeongseon Lee, Omesh Tickoo, Nilesh Ahuja, Mahesh Subedar, Galina Ryvchin Intel Labs, Intel Corporation
11:20 AM 11:45 AM   A Real-time System for Multi-Person Hospital Action Recognition and Fall Detection Srenivas Varadarajan, Omesh Tickoo Intel Labs
11:45 AM 1:15 PM                                                                  Lunch break
1:15 PM 2:10 PM Keynote: Robots Learning from Human Teachers Dr. Andrea Thomaz Electrical and Computer Engineering, UT Austin
2:10 PM 2:35 PM   A Smart Fog Gateway for Wearable IoT Devices Nick Constant, Kunal Mankodiya Electrical, Computer & Biomedical Engineering
The University of Rhode Island
2:35 PM 3:00 PM   Optimizing Sensor-Cloud Architectures for Real-time Autonomous Drone Operation Hasan Genc, Ting-Wu Chin, Matthew Halpern, Vijay Janapa Reddi The University of Texas at Austin
3:00 PM 3:30 PM                                                                         Break
3:30 PM 3:55 PM   Towards Dynamic, Isolated Work-groups for Distributed IoT and Cloud Systems with Peer-to-Peer Virtual Private Networks Kensworth Subratie, Saumitra Aditya, Sebastian Sabogal, Teja Theegala*, Renato Figueiredo ACIS Laboratory, Electrical and Computer Engineering, University of Florida, *Google Summer of Code 2015
3:55 PM 4:20 PM   A Cross-Platform library for I/O and Sensors Brendan LeFoll, Ajay Mungara,
Ramesh Peri
Intel Corporation
4:20 PM 4:45 PM   Tiny and Fast Root of Trust for IoT Edge Devices Li Zhao, Rafael Misoczki, Santosh Ghosh, Manoj Sastry Intel Labs

 

  Below is the proposed list of topics for the workshop.  Topics include, but are not restricted to, the following:

Sensors, Actuators, Gateway & Controllers Architectures

– Architectures for wearable and IOT devices
– Heterogeneity in Cores, Frequency, Cache, Memory
– Power, Performance, Energy optimizations
– SoCs, CPU/GPU, CPU/GPGPU architectures
– Ultra-Low Power Core Micro-architectures
– Fabrics / Network-on-chip, Cache/Memory Hierarchies
– HW Support for Heterogeneity, Programmability, Modularity
– Simulation / Emulation Methodologies
– Protocols and abstraction layers (MQTT, CoAP, REST, …)

Cloud Architecture

– Data Center Architectures for IoT; customization and specialization
– Edge/Fog computing – Dynamic Cloud-gateway-device offloads
– Workload/Algorithm  Partitioning between Heterogeneous Cores and Accelerators
– BigData Frameworks (Hadoop, Spark, Flink, …)
– Heterogeneous Datacenters (FPGA, GPU, Accelerators, …)
– Machine Learning Algorithms & Applications, Graph processing, Deep Neural Networks
– Batch, streaming and distributed Analytics
– Design Patterns and Application Programming frameworks

Emerging Workloads and Use cases

– Wearable and IOT use cases and workloads
– Speech/Image recognition and understanding, Cognitive computing
– Personal Assistants, Predictive/Prescriptive Analytics, Robotics
– Workload Analysis for power/performance/energy optimization and acceleration
– Performance Monitoring and Simulation, Architecture analysis

Novel Accelerator Designs

– Specialized Accelerator Architectures and Designs
– Machine Learning, Neural Network and Graph Processing accelerators
– Domain-Specific Programmable/Configurable Accelerators
– Accelerator Interfaces for Programmability
– Development Environments for Accelerator Design 

Submission Guidelines: Interested authors are encouraged to submit extended abstracts (1 – 2 pages) or short papers (6 pages) by email to the organizing chairs. The deadline for submission is December 16, 2016. Final (short) papers will be due on Jan 16, 2017.

Important Dates:

Abstract/Paper submission: December 16, 2016
Author Notification: January     02, 2017
Final Paper Submission: January     16, 2017
Workshop: February    04, 2017